In semiconductor wafer processing, advanced process control (APC) refers to the selective adjustment of one or more process specifications for a particular process based on feedback in order to achieve a target parameter value in each of multiple instances of the same feature in a pattern when the particular process is repeated on the same semiconductor wafer or a different semiconductor wafer. For example, APC can be performed for a particular process (e.g., a photolithography process or an etch process) used to form a patterned region with a pattern of features (e.g., 200+ features) on a semiconductor wafer. Specifically, APC can be performed in an attempt to achieve a target parameter value in each of the features. The target parameter value can be, for example, a critical dimension. For purposes of this disclosure, the term “critical dimension” refers to a minimum size of a feature (e.g., a minimum width of a feature).
Generally, APC involves performing the particular process according to an initial set of process specifications. If a determination is made that a target feature (i.e., a selected one of the features from the pattern) does not have the target parameter value, then at least one of the process specifications is adjusted for use when the particular process is subsequently repeated to form the same patterned region elsewhere on the same semiconductor wafer or on another semiconductor wafer. However, the actual parameter value of a single target feature selected from amongst all of multiple features (e.g., 200+ features) in the patterned region may not be representative of the majority of the features. For example, the actual parameter value for a single target feature may be relatively small or large as compared to the parameter values of other features in the patterned region. As a result, process specification adjustments made based on that actual parameter value of the target feature may result in an overcorrection. For example, if the target feature is relatively small, adjustments made to a process specification based on that target feature could result in subsequently patterned features being too large, whereas if the target feature is relatively large, adjustments made to the same process specification based on that target feature could result in subsequently patterned features being too small.
One technique that has been used in an attempt to avoid such an overcorrection is to make the adjustments to the process specification(s) based on an average of the measurements taken from a sample of target features (e.g., 2-5 target features) selected from the pattern. Unfortunately, the average of such a small sample, when the total number of features is high (e.g., in the hundreds), also may not be representative of the majority of the features such that process specification adjustments made based on that average may not be optimal.